HOW HYDROLOGICAL DATA COULD PROTECT YOU FROM WEST NILE VIRUS

Despite apparent advances in the control of infectious diseases, mosquito-borne diseases have grown to become an enormous threat to humans. Our focus here is with West Nile Virus (WNV), the most common mosquito-borne disease in the U.S. Understanding this disease is complicated by the complex transmission dynamics involving mosquitoes, birds, and humans. The public health burden is substantial because it can cause neurological damage and there is no vaccine available for humans. Previous studies have explored the influence of climate on mosquito numbers in order to predict WNV infections in humans. The simple assumption is that the numbers of human cases increase with increasing mosquito numbers. However, outbreaks can occur when mosquito abundance is low. In addition, the studies often dismiss the hydrological understanding of small wetlands as potential breeding sites for mosquitoes by focusing only on local weather patterns. In order to investigate the relationship between the numbers of mosquito and infected humans, we conducted a spatial-temporal statistical analysis in a part of the northern Great Plains (North Dakota and nearby states) in where the highest infection rates in the U.S. are reported.

Our study approach is unique in statistically modeling the numbers of mosquitoes and human disease cases, independently. In addition, this was a few studies which suggested the importance of incorporating the knowledge of hydrology for the analysis of mosquito-borne disease. The statistical simulation of mosquito abundances identified the importance of rainfall intensity and it showed that moderate rainfall events during the spring creates suitable habitat for mosquito to breed. In addition, the river flooding caused by regional snow-melt and runoff significantly reduced the numbers of mosquito along the flooding plains. This suggests more mechanistic approach is crucial to identify the water body type in order to develop a spatial model for mosquito dynamics. Our analysis also revealed that the disease was apparent when the temperature was high, even mosquito abundance was low in the area. Individually assessing the dynamics of the mosquito abundance and the disease cases provided a better understanding of disease transmission dynamics.